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Tuesday, January 12 at 2 p.m. via Zoom
Speaker: Dr. Ryan McCarty, UC Irvine, Chemistry
Abstract: Convergence research aims to solve “complex problems focusing on societal needs,” but spanning the historic divisions of academic disciplines poses problems complex in their own right. Machine learning leverages disciplinary diversity by bridging data and insight from across STEM disciplines. Drawing on algorithms from chemometrics and computer science, my research derives physical insight by using machine learning to "reverse engineer" electronic structure from quantum modeling outputs and experimental spectra. This talk will highlight examples of this approach used to identify chemical warfare agents and understand the nature of electron exchange and correlation as estimated by density functional theory.